Invasion prediction with artificial intelligence in ductal carcinoma in situ (DCIS) patients: a proof-of-concept study.

ABSTRACT:

Background

Ductal carcinoma in situ (DCIS) is a heterogeneous precursor lesion with variable invasive potential. Current predictive parameters for invasion risk offer limited utility for personalized assessment. This study aims to evaluate artificial intelligence (AI)-assisted mammography analysis as a tool for predicting invasion risk in DCIS patients.

Methods

In this retrospective cohort study, 74 patients with pathologically proven DCIS by preoperative biopsy were analyzed using a deep learning-based AI system (Transpara version 1.7.4). The AI system classified patients into low-risk and high-risk groups, which were validated against postoperative histopathological findings. Statistical analysis included sensitivity, specificity, positive predictive value (PPV), negative

SUBMITTER: Gundogdu A 

PROVIDER: S-EPMC12542369 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature